ResGenXAI 2025 : 2025 IEEE International Conference on Responsible, Generative and Explainable AI
The “International Conference on Responsible, Generative and Explainable AI (ResGenXAI-2025)” is a newly initiated conference focusing on high-quality research articles that are quality-checked through peer review and published in IEEE Xplore. The scope of the conference is multidisciplinary in the domain, focusing on recent advancements in artificial intelligence. The conference scope includes the Responsible AI Track, Generative AI Track, and Explainable AI Track.
Papers in the main technical program must describe high-quality, original research.
The topics of interest include but are not limited to :
Responsible AI Track:
Ethical AI Frameworks and Principles
Fairness, Bias, and Diversity in AI
AI Safety, Robustness, and Reliability
Privacy-Preserving AI and Data Protection
Algorithmic Accountability and Transparency
Human-Centered AI and User Interaction
Regulatory Landscape and Governance of AI
Environmental Sustainability in AI
Cross-Disciplinary Perspectives on Responsible AI
Generative AI Track:
Advances in Generative AI
Generative AI in Healthcare and Medicine
Generative AI for Content Creation and Entertainment
Generative AI in Design and Creativity
Generative AI for Personalization and Recommendation Systems
Generative AI for Electrical Applications
Explainable AI Track:
Explainable AI: Methods and Applications
Fairness, Bias, and Diversity in AI
Privacy-Preserving AI and Data Protection
Algorithmic Accountability and Transparency
Human-Centered AI and User Interaction
Papers in the main technical program must describe high-quality, original research.
The topics of interest include but are not limited to :
Responsible AI Track:
Ethical AI Frameworks and Principles
Fairness, Bias, and Diversity in AI
AI Safety, Robustness, and Reliability
Privacy-Preserving AI and Data Protection
Algorithmic Accountability and Transparency
Human-Centered AI and User Interaction
Regulatory Landscape and Governance of AI
Environmental Sustainability in AI
Cross-Disciplinary Perspectives on Responsible AI
Generative AI Track:
Advances in Generative AI
Generative AI in Healthcare and Medicine
Generative AI for Content Creation and Entertainment
Generative AI in Design and Creativity
Generative AI for Personalization and Recommendation Systems
Generative AI for Electrical Applications
Explainable AI Track:
Explainable AI: Methods and Applications
Fairness, Bias, and Diversity in AI
Privacy-Preserving AI and Data Protection
Algorithmic Accountability and Transparency
Human-Centered AI and User Interaction